def __init__(self,df,host,measurement,look_back,nb_layers,loss,metric,nb_features,optimizer,nb_epochs,nb_batch,form,freq_period) :
Predictor.__init__(self)
self.df=df
self.host=host
self.measurement=measurement
self.form=form
self.freq_period=freq_period
trend_x, trend_y,seasonal_x,seasonal_y,residual_x,residual_y=self.prepare_data(df,look_back,self.freq_period)
model_trend=self.make_models(nb_layers,loss,metric,nb_features,optimizer,True)
model_seasonal=self.make_models(nb_layers,loss,metric,nb_features,optimizer,False)
model_residual=self.make_models(nb_layers,loss,metric,nb_features,optimizer,False)
model_trend=self.train_model(model_trend,trend_x,trend_y,nb_epochs,nb_batch,"trend")
model_seasonal=self.train_model(model_seasonal,seasonal_x,seasonal_y,nb_epochs,nb_batch,"seasonal")
model_residual=self.train_model(model_residual,residual_x,residual_y,nb_epochs,nb_batch,"residual")
self.model_trend=model_trend
self.model_seasonal=model_seasonal
self.model_residual=model_residual
def __init__(self, df, host, measurement, look_back, nb_layers, loss,
metric, nb_features, optimizer, nb_epochs, nb_batch, form,
freq_period):
Predictor.__init__(self)
self.df = df
self.host = host
self.measurement = measurement
self.form = form
self.freq_period = freq_period
trend_x, trend_y, seasonal_x, seasonal_y, residual_x, residual_y = self.prepare_data(
df, look_back, self.freq_period)
model_trend = self.make_models(nb_layers, loss, metric, nb_features,
optimizer, True)
model_seasonal = self.make_models(nb_layers, loss, metric, nb_features,
optimizer, False)
model_residual = self.make_models(nb_layers, loss, metric, nb_features,
optimizer, False)
que = queue.Queue()
threads_list = list()
thread = Thread_train_model(model_trend, que, trend_x, trend_y,
nb_epochs, nb_batch, "trend",
"Trend Thread")
thread.start()
threads_list.append(thread)
thread_1 = Thread_train_model(model_seasonal, que, seasonal_x,
seasonal_y, nb_epochs, nb_batch,
"seasonal", "Seasonal Thread")
thread_1.start()
threads_list.append(thread_1)
thread_2 = Thread_train_model(model_residual, que, residual_x,
residual_y, nb_epochs, nb_batch,
"residual", "Residual Thread")
thread_2.start()
threads_list.append(thread_2)
for t in threads_list:
t.join()
self.model_trend = que.get(block=False)
self.model_save(self.model_trend, "trend")
self.model_seasonal = que.get(block=False)
self.model_save(self.model_seasonal, "seasonal")
self.model_residual = que.get(block=False)
self.model_save(self.model_residual, "residual")
